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Neural network: What it can do for petroleum engineers

Journal Article · · JPT, Journal of Petroleum Technology; (United States)
DOI:https://doi.org/10.2118/29219-PA· OSTI ID:6683910
 [1]
  1. West Virginia Univ., Morgantown, WV (United States)
Neural network, a nonalgorithmic, nondigital, intensely parallel and distributive information processing system, is being used more and more every day. The main interest in neural networks is rooted in the recognition that the human brain processes information in a different manner than conventional digital computers. Computers are extremely fast and precise at executing sequences of instructions that have been formulated for them. Once the network has learned the information in the training set and has converged,'' the test set is applied to the network for verification. It is important to note that although the user has the desired output of the test set, it has not been seen by the network. This ensures the integrity and robustness of the trained network. Neural networks have proved to be valuable pattern-recognition tools. They are capable of finding highly complex patterns within large amounts of data. A relevant example is well log interpretation. It is generally accepted that there is more information embedded in well logs than meets the eye. Determination, prediction, or estimation of formation permeability without actual laboratory measurement of the cores or interruption in production for well test data collection has been a fundamental problem for petroleum engineers. From geophysical well log data, it was possible to predict and/or estimate permeability of a highly heterogeneous formation in West Virginia.
OSTI ID:
6683910
Journal Information:
JPT, Journal of Petroleum Technology; (United States), Journal Name: JPT, Journal of Petroleum Technology; (United States) Vol. 47:1; ISSN 0149-2136; ISSN JPTJAM
Country of Publication:
United States
Language:
English